Are Test Collections “Real”? Mirroring Real-World Complexity in IR Test Collections

Abstract

Objective evaluation of effectiveness is a major topic in the field of information retrieval (IR), as emphasized by the numerous evaluation campaigns in this area. The increasing pervasiveness of information has lead to a large variety of IR application scenarios that involve different information types (modalities), heterogeneous documents and context-enriched queries. In this paper, we argue that even though the complexity of academic test collections has increased over the years, they are still too structurally simple in comparison to operational collections in real-world applications. Furthermore, research has brought up retrieval methods for very specific modalities, such as ratings, geographical coordinates and timestamps. However, it is still unclear how to systematically incorporate new modalities in IR systems. We therefore propose a categorization of modalities that not only allows analyzing the complexity of a collection but also helps to generalize methods to entire modality categories instead of being specific for a single modality. Moreover, we discuss how such a complex collection can methodically be built for the usage in an evaluation campaign.